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dc.contributor.authorPanahi, Milad
dc.contributor.authorBehrangi, Ali
dc.date.accessioned2020-07-14T20:48:29Z
dc.date.available2020-07-14T20:48:29Z
dc.date.issued2019-12-13
dc.identifier.citationPanahi, M., Behrangi, A. Comparative Analysis of Snowfall Accumulation and Gauge Undercatch Correction Factors from Diverse Data Sets: In Situ, Satellite, and Reanalysis. Asia-Pacific J Atmos Sci (2019). https://doi.org/10.1007/s13143-019-00161-6en_US
dc.identifier.issn1976-7633
dc.identifier.doi10.1007/s13143-019-00161-6
dc.identifier.urihttp://hdl.handle.net/10150/641853
dc.description.abstractDespite its importance for hydrology and water resources, accurate estimation of snowfall rate over snow-covered regions has remained a major observational challenge from both in-situ and remote sensing instruments. Snowfall accumulation can be measured by either accumulating snowfall estimates or measuring snowpack properties such as Snow Water Equivalent (SWE) and mass. By focusing on snowfall over snow accumulation period and using case studies and long-term average (2003 to 2015) over CONUS, this study compares snowfall accumulation from gauge stations (using GPCC and PRISM products), satellite products (GPCP and the suite of IMERG products), and reanalysis (ERA-interim, ERA5, and MERRA-2). Changes in SWE based on the recent UA-SWE product together with mass change observation from GRACE were used for assessment of precipitation products. We also investigated two popular gauge undercatch correction factors (CFs) used to mitigate precipitation undercatch in GPCC and GPCP. The results show that snow accumulation from most of the products is bounded by GPCC with and without correction, highlighting the critical importance of selecting proper CFs for gauge-undercatch correction. The CF based on Legates and Willmott method was found to be more consistent with the SWE-based analysis than CF based on the Fuchs method. Reanalysis show very similar spatial pattern among themselves, but represent large variation in simulating snow accumulation, with ERA-interim showing the least accumulation and MERRA-2 showing the highest accumulation and closest to the snow accumulation suggested by SWE.en_US
dc.language.isoenen_US
dc.publisherKOREAN METEOROLOGICAL SOCen_US
dc.rights© Korean Meteorological Society and Springer Nature B.V. 2019.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectSnowfallen_US
dc.subjectSWEen_US
dc.subjectGauge undercatchen_US
dc.subjectSatelliteen_US
dc.subjectReanalysisen_US
dc.titleComparative Analysis of Snowfall Accumulation and Gauge Undercatch Correction Factors from Diverse Data Sets: In Situ, Satellite, and Reanalysisen_US
dc.typeArticleen_US
dc.identifier.eissn1976-7951
dc.contributor.departmentUniv Arizona, Dept Hydrol & Atmospher Scien_US
dc.contributor.departmentUniv Arizona, Dept Geoscien_US
dc.identifier.journalASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCESen_US
dc.description.note12 month embargo; published online: 13 December 2019en_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal accepted manuscripten_US
dc.identifier.pii161
dc.source.journaltitleAsia-Pacific Journal of Atmospheric Sciences


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